What I Learned at the Customer Data Platform Workshop

I ran a four hour workshop on Customer Data Platforms this week at the MarTech Conference in San Jose.* The attendees were a mix of marketers and technologists from brands, agencies, and vendor companies. We had surveyed them in advance and found, not surprisingly, goals ranging from understanding CDP market trends to optimizing data loads for technical performance. The agenda was correspondingly varied and I like to think that everyone learned something useful.  Based on attendee comments and my own observations, here’s what I myself learned.

- CDP is a vague category. This was voiced with some frustration at the end of the workshop, when several people said they had hoped to come away with a clear picture of what is and isn’t a CDP, but found instead that CDP systems differ widely. In the context of the workshop, I actually considered this to be a positive result: one of the main points I tried to get across was that CDPs have very different features and picking the right one requires you to first understand your own needs and then look carefully at which systems have the features needed to meet them.  Complaining about it is like going to a workshop on car buying and discovering that automobiles differ widely: if you didn't understand that before, you couldn’t possibly have made a sound choice. The variety may seem overwhelming but once you recognize it exists, you’re ready to take the next step of figuring out how to find the capabilities that match your needs.

- People want CDP-specific use cases. I knew in advance that people want to understand CDP use cases. This has become a very common question in the past year and the CDP Institute Library includes many papers on the topic. My personal problem has been that CDPs are like bacon: they make everything better. This made it seem silly to list use cases, because the list would include pretty much any marketing project that involves data. What I learned from the workshop is people are really looking for use cases that only become possible with a CDP. That’s a much different and more specific question: What can I do with a CDP that can’t do without one?

We discussed the answers as a group at the end of the workshop and the main conclusion was CDP makes possible many cross-channel activities that are otherwise impossible because cross-channel data isn't unified.  This isn’t exactly news – unified customer data is the whole point of a CDP – but it’s still good to focus specifically on the use cases that unification makes possible.

On reflection, I’d add the CDP also exposes data that’s otherwise trapped in source systems or not collected at all. This could be information from a single channel, so it’s distinct from the cross-channel use case. Our workshop group didn’t mention this one, so I’ll have to stress it more in the future.

The group also didn’t list the operational efficiencies of a CDP as unique benefits. That’s interesting because so much of our discussion stressed the lower cost, faster deployment, and lower risk of CDP compared with other solutions. Apparently that’s either not credible or not important. I’ll speculate that the technicians didn’t believe it and the marketing people didn’t really care. But of course that’s utterly unsupported stereotyping. (Speaking of stereotyping, I’m pretty sure the technical people sat in the back rows and the marketers talked a lot more during the small group discussions.  Next time I'll make them wear labels so I know for sure.)

- Marketers don’t care about technical details. Ok, that's really unfair stereotyping so let's change it to “some marketers”.  But it’s definitely fact-based: one of marketers complained as we started to drill into the technical parts and several others agreed. I pushed back a bit, arguing that you can’t make a sound system selection without looking at technical differences. I think I was polite about it, but have strong feelings on the subject: lack of research into specific product capabilities is by far the biggest reason people end up unhappy with a software purchase. (Yes, I have research to back that up.)

I suppose the counter-argument is what really matters are the functional differences and not the technical methods used to accomplish them. My counter-counter-argument would be the technical methods matter because they determine how efficiently a system executes those functions and how easily it can extend them. Architecture is destiny, as it were.  In my mind, the argument ends there and I win but maybe there’s more to be said for the other position. (If case you’re wondering, I did speed through the technical parts after that objection, and talked more about use cases instead. Squeaky wheels get the grease. And there was a later part of the agenda that circled back to technical questions anyway.)

So, that’s what I learned during the workshop. As you might imagine, preparing it forced me to think through several topics that I’ve been addressing casually. I’m most pleased with having clarified the relationships among strategy, marketing programs, use cases, resources, and requirements. The image below summarizes these: as you see, strategy drives marketing programs which drive resource needs**, while marketing programs drive use cases which drive system requirements. Those are two sets of objects that I usually discuss separately, so I’m happy to finally connect them. Plus, I think it’s a cute picture. Enjoy.

_______________________________________________________________________________________
* I'll likely be repeating it elsewhere over the next few months.  Let me know if you're interested in attending.

** The flow can also run the other way: available resources determine what marketing programs you can run which determine what strategy makes the most sense.

Open Letter to Scott Brinker: Suggestions for Next MarTech Conference

Dear Scott:

Congratulations to you and Third Door Media on another great MarTech conference. (And, as an aside, I’m astounded that you found time to write a blog post on the Stackies within a day of the conference ending. Do you NEVER sleep?)

I think I’m still technically on the advisory board for this conference, so I thought I’d share some thoughts. To encourage input from the larger community, I’m posting it publicly on this blog. You’re welcome.

Over-all, the conference went tremendously well. Attendees I spoke with were uniformly pleased with the quality of the presentations. The closest thing I heard to a criticism was that some sessions were more theoretical than action-oriented, but that is really a matter of taste. One person told me he liked the case studies best; no surprise there. Someone else said they were surprised at how many had a B2C focus, although that was more an observation than a complaint. The only frustration I heard consistently was having to choose between two interesting sessions when they were on at the same time.

From my own perspective, the worst thing was that no one laughed at the cave man joke.  Unga bunga bink! I did feel the exhibit hall was more crowded than optimal, although some vendors seemed to like being able to grab attendees as they walked by.  I’ll also complain that many vendors lacked signage that explained what they did – not your fault, of course, and maybe a conscious strategy to force people to engage?   Perhaps we could have one of the automated content generation vendors read all the vendor materials and write optimal signs for them!

On to suggestions for next year. I expect you’ll go to even more tracks, which will make it still harder to choose which to attend. Video recordings would let people catch up on sessions they missed; if that’s too expensive, voice recordings to accompany the slides would be a big help.

Maybe a better delineation among the tracks themselves would help too. I’d love to see a track of sessions analyzing product groups within the big landscape: i.e., one for marketing automation, one for content marketing, one for marketing analytics, etc. That would also be a good way to segregate analysts like me from people who want to avoid them. You might also have separate technology and organization tracks and maybe even have an ad tech track (a very underrepresented topic this year). If things get really big, you could also split B2B vs B2C or enterprise vs. SMB. The idea would be to find categories that are more or less mutually exclusive in terms of their audience, although of course some cross-over would be expected and a Good Thing.

Another way to help people with narrow interests would be to have special interest groups, such as ‘birds of feather’ tables at lunch or open-mike roundtables during sessions. I could see tables for CMOs, CMTOs, CTOs, marketing ops, newbies, and other peer groups with their own sets of challenges.  Or maybe separate bar set-ups during the receptions.

Speaking of social interaction, I still think the conference could do more to help people have fun. I’ve suggested this before but would still like to see 30 second videos submitted by attendees on topics like “tall tales I've heard from vendors”, “organizational horror stories”, “if people said what they really thought” (video of a typical meeting with thought bubbles showing people's real thoughts), or pitches for an imaginary, absurd martech product. People could do these in advance or have an opportunity to record them during the show. You’d show the best ones in between speeches or on a loop in the exhibit hall. I suspect there are some really hilarious MarTech folks out there. (Heck, I know there are – I’ve seen some of their project plans.)

I could also see some more conventional competitions in the exhibit hall. These would be team sports, so you could have marketing vs. IT, big companies vs. little companies, vendors vs buyers, etc. Or maybe mixed teams to practice their alignment skills. Picking a sport is tough: foosball is obvious but might give an unfair advantage to the IT folks. We could balance that with something that marketers are especially good at – maybe darts, which I believe are still the standard tool for setting media budgets. Just a thought.

There’s always Powerpoint karoke, although that’s best for after hours.

Or let’s get really high tech. We could have a speech recognition vendor listen to the presentations and score them for buzzword bingo. Or, at least, do a word cloud of what people are saying, either in speeches or in Twitter comments. We could have a competition among speakers for the most Tweets (although I guess that already happens).

Back to team sports. How about teams of attendees competing to create the most successful marketing campaign during the conference? We’d have vendors create preintegrated stacks with tools for research, content creation, campaign execution, optimization, and analytics. The vendors and team members would design, execute and optimize their campaigns, which shouldn’t take much time if the systems are really efficient. Two days is enough time to get some initial results. The campaigns could be for imaginary products or, better still, for worthy charities. Attendees could form their own teams or we could let something like CrystalKnows profile them and then assign attendees to teams with a good balance of skills and personalities.

If that’s too complicated, we could do a standard bake-off competition where vendors and novice users are given a simple task (e.g., create an survey or dynamic email) and do it while everybody else watches and then votes on the results.

Looking forward to next year!

Best,

David

MarTech Madness: Marketing Technology Managers Come Out to Play in San Francisco

MarTech Madness hit this week in San Francisco as 1,200 delighted marketing technologists escaped from their cubicles to cavort under the genial gaze of @chiefmartec Scott Brinker at the latest MarTech Conference. My own experience was a bit skewed because I was pulled into many side meetings, but the attendees seemed pleased and the sessions I did attend were excellent as always. MarTech is unique in its focus on the process of marketing technology management, with sessions covering organizational, staffing, and training issues even more than the technology itself. It’s also unusual in attracting people from both B2B with B2C companies, two groups that rarely mix.

As usual, I spent much of my conference time prowling the exhibition booths. I was struck by the number of content-related exhibitors – nearly half, based on my analysis of the conference program. Many of those were doing standard content management tasks such as workflow, approvals, and repository management.  But several offered some kind of interactive content, which I’d define as content that captures information about the user either through recording behaviors or explicitly asking for input (HapYak, ion interactive, LookBook HQ, SnapApp, and arguably Uberflipand Vidyard). This is a category that also caught my eye at the Content2Conversion conference last month.  Two mentions officially makes it a trend.

There were also several vendors doing what I’ll tentatively call “journey management” (Pointillist, Usermind, Thunderhead [represented at the conference by its partner Arke], and arguably IBM Journey Designer). These resemble conventional campaign managers but execute campaigns based on movement through a comprehensive journey map. These products differ from the earlier generation of journey managers in being tied to live customer data and execution systems, rather than simply drawing a map. There’s considerable variety among these vendors so I need to analyze them more closely before I can confidently call them a meaningful category. But seeing several products emerge simultaneously with similar features is usually a sign that something interesting is afoot.

As these observations suggest, many of my conversations during the conference – especially after the bars were open – related to the ever-popular game of What’s The Next Big Thing? The spotlight has clearly moved from predictive analytics.  ABM is still the current focus but it’s starting to feel dangerously familiar. Interactive content and journey management are definitely candidates, but the consensus at the deepest (and best lubricated) discussion seemed to be what you might call user-tuned content* – that is, content that adjusts to the viewer’s behavior, presumably using artificial intelligence to choose what to do next. That’s different from capturing behaviors with interactive content, as described above, although the same system could do both: in fact, I'd put LookBook HQ in both categories.

"User-tuned content" appeals to me in part because my own MarTech presentation was on machine intelligence, and one strand of development I foresee is combining systems that recognize an individual customer and select the best product or offer (e.g. Evergage or BlueConic); identify the customer's persona (e.g. CrystalKnows, Mariana, CaliberUX); and automatically write data-driven content tuned to that persona (Automated Insights, Narrative Science, Data2Content, and Arria). Concretely, imagine an ecommerce Web site that gives each customer different product descriptions based on her personality. That’s a step beyond current personalization or recommendation engines, which select the best message or product but don’t change how it's presented or use manually-created variations.  It’s also a step closer to what a good human salesperson does, tailoring their presentation to whatever they feel will best resonate with the person they’re talking to.

The pieces needed to deliver user-tuned content are all available, although I haven’t seen any one vendor combine them into a single product. Maybe that won’t happen soon enough to the very next Big Thing, but I’m pretty sure it will be a Big Thing in the not too distant future.

_______________________________________________________________________
*I really wanted to call this "smart content", but that's used by HubSpot for something else.  "Intelligent content", "responsive content", "contextual content", "dynamic content", "personalized content", "tailored content" and many others are also taken.  "User-tuned content" has been used in pretty much the sense I have in mind, although specifically relating to content tuned to the needs of autistic children.

Marketing Technology of the Future: Beyond the Customer Data Platform

The last three minutes of my MarTech Conference presentation are driving me crazy.

The preceding portions cover the current state of Customer Data Platforms. I have no trouble talking about that. But it somehow got into my head that the last section should look at how CDPs will fit into the long-term future of marketing technology. I have some fuzzy notions that this future martech will be radically different from today.  But to cover it succinctly I must first think it through in detail. That has been considerably harder than I expected. Here’s what I have so far.

Current Trends

These are developments happening now that will provide the context for industry changes. Some will be the topic of other MarTech presentations.

• Convergence of Adtech with Martech. These have until recently been largely separate: Adtech deals with messages to audiences whose members may share common characteristics but are not individually identified. Martech deals with known individuals. As anonymity becomes increasingly unavailable, marketers will know exactly who is receiving their advertising messages. Martech targeting techniques will therefore be used in adtech as well. Conversely, some adtech features will become standard martech practice.  More about that later.

• Contextual data. Social networks, mobile devices including phones and wearables, and the Internet of Things will provide ever-more details about the precise situation of each customer during each interaction.  Location is an obvious data point, but marketers will also know your local weather, your mood and physical condition, what you’re wearing, when and what you last ate, and whether your car needs gas. This may sound seriously creepy but the good news is you’ll get better-targeted messages.  I’d love to call this “contextual marketing” but that term is taken.

• Marketing to machines. I’m not talking about marketing with machine-generated data (e.g., your running shoes telling Nike how many miles you’ve logged) or marketing through messages on your machine (your washer suggesting you buy Tide-brand detergent).  I’m talking marketing to machines that are making purchase decisions on their own.  I discussed this last year in Do Self-Driving Cars Pick Their Own Gas Stations? and More on Marketing To Things.  Frankly, I've been surprised to see little else written on the topic. Trust me, this will be big: imagine convincing Siri to recommend your restaurant every time someone asks where they should go to lunch.

Implications for Martech

Given the trends I’ve just listed, I see martech changing significantly.

• Data synergy. I just made that term up but the idea is old: related bits of data are worth more when they’re combined. So knowing you just booked a trip to Alaska and knowing you just walked into a department store are each marginally useful by themselves, but together they let you offer me a great deal on a warm coat. It helps even more if I know you don’t already have one. The implication of this is that there’s a lot of value gained from combining data from different sources into shared repositories. It also implies there’s a lot of value in “identity association” technologies that link related data to the same person.  If you've been wondering why companies like Oracle, Acxiom, and Nielsen have been buying big data aggregators, you can stop.

• Everything is biddable. Another implication of data synergy is that each opportunity to communicate with an individual will be much more valuable to some people than others. Let’s stick with that Alaska trip: selling you a coat might be worth less than selling you a hotel room. So, when you walk into the store, the hotel chain might be willing to pay more for the chance to send you a message than the store itself. Having all the messaging devices connected to a central database and bidding system makes this possible – in fact, it already happens with real time bidding on Web ads. Now Martech platforms get to do the same. And oh, to make this work well, Martech has to hugely improve its ability to measure the actual impact of each message – so advanced, predictive attribution also plays a leading role in the martech world of the tomorrow.

• Campaigns are dead but the customer journey lives on. If each interaction is bid separately, then the notion of campaigns that lead the customer through a sequence of contacts on a flow chart is irrelevant. Honestly, I’m glad to see it go: the very first campaign management system I saw, more than twenty years ago, had exactly that sort of interface and it’s well past time for a change. But this doesn’t mean we can stop thinking about customer journeys. Any model that supports bidding on individual messages must understand where each customer is in her journey and how the message will influence the result.  Of course, different marketers will be tracking different journeys.

• Automation takes over. It’s obvious that mass data consolidation, real time bidding, optimized messaging, and omnichannel execution require near-total automation of the entire process. This has to be really intelligent automation that finds patterns, notices when they change, and optimizes treatments with minimal human guidance. And where will all that highly tailored content come from? You guessed it: automated content creation systems, which are more common and further advanced than you may realize. See Paul Roetzer’s recent post on artificial intelligence in marketing automation for an introduction to the topic  and watch Humans Need Not Apply if you want to get really scared.

• Machines buy martech. If the over-all trend is machines selling to other machines, why should  martech be left out? In fact, testing the huge number of new martech options (or even generating Scott Brinker's martech landscape supergraphic) is something machines could do really well. Once suitably open architectures are in place, it should be easy to plug in new components like a better predictive modeling system, new type of video promotion, or the latest social media app. Even if those components are less than fully automated, they could be identified, screened, integrated, and assessed with minimal human intervention.  Machines would almost surely assess results better than humans, since they’d be more objective and better able to look for subtle effects on customer behavior than human analysts.

• Humans keep things running. It’s possible that machines will eventually control every aspect of our marketing.  But I think humans will have a role to play at least for a while. This won’t necessarily be the traditional “creative” work such as copywriting and design, which machines already do better than we care to admit. But they’ll still need people to come up with non-incremental products, non-obvious insights, and deals with other organizations. Even things that machines could do better than people won’t be wholly machine-run for a while, just due to the normal lags in technology and organizational development. This may sound like a dark view of humanity’s future, but I’m more optimistic than it seems. Technology never works quite as well as promised, so I figure humans will still be needed to keep things running.

Implications for Marketers

If Martech moves in the directions I’m proposing, marketers need to do certain things to prepare.

• Expect imperfection. Sure we’ll have vastly more data than ever, but don’t assume it will be perfectly complete, accurate, or integrated. In fact, you can guarantee it won't.  Predictive models make mistakes as well. Look for systems that are designed to accommodate incomplete information, check for differences between actual and expected performance, and adapt gracefully to failures. Above all, demand transparency so you can see what the automated systems are doing and have some idea of why. This will probably require help from other systems, but make sure the monitors are as independent as possible so they’re not fooled by shared mistakes. If you’re really feeling clever, examine imperfections for opportunities – you may find bargains in bidding on messages to customers that other systems have rejected because their data is unavailable or contradictory.

• Plan for change. As anyone who has tried to modify a complex campaign workflow already knows, sophisticated systems can be brittle. High performance automated systems are likely to optimize themselves for specific conditions, which is great until those conditions change. Be sure you can easily introduce new data sources, components, objectives, and execution channels. And be sure you can always revert to a simpler, more manual mode of operation if things really go bad.

• Focus on the analytics layer.  One implication of data synergy is that the richest databases will live outside of your company’s own data center: they’ll be too big, too complicated, and updated too frequently to maintain a copy in-house. Similarly, if companies are bidding to deliver messages everywhere a customer appears, they won’t own the touchpoints. So the only piece the company can expect to own is the analytical layer – the bidding and content engines. Those engines should be freely swappable as well. What’s left to hold things together is a core of profile data shared by the analytical and content engines. This is connected to the external data store on one end and the touchpoint systems on the other. All told, it’s a rather wispy little framework, but it should be enough to provide the glue needed to link all the other components.

So, where does that leave us?  Gigantic external data pools linked to personal identities, real time bidding, messages delivered through paid channels: it's "adtech without the privacy" if you want to put it in a nutshell.  That isn't where I expected to end up, but that's exactly why I needed to write this. I can’t guarantee I won’t change my mind after further reflection, but for now I think this gives a reasonable picture of what martech might look like five or ten years from now.  In the shorter term, I still expect the central role will be played by Customer Data Platforms or (more likely) by Marketing Platforms that combine the data parts of a CDP with a multi-purpose analytical and decision layer.

Now all I have to do is figure out how to cram this into three minutes. 

...hmm...

On further reflection, it comes down to a hybrid of martech plus adtech, which is inevitably named madtech:

Do Self-Driving Cars Pick Their Own Gas Stations?

I had a delightful and well-lubricated dinner this week with Scott Brinker of @chiefmartec fame, ostensibly to discuss the next edition of the MarTech Conference but mostly just to chat about the industry and what comes next.

Scott wasn’t too impressed by my notion of an advertising-supported toaster (see my last blog post), even though I pointed out you could segment the messages based on the type of bread the person was eating. On the other hand, I was very intrigued by his notion of marketing through services such as alerting a driver when they need gas and where to find the most suitable gas station.

Where that example got interesting was when we added self-driving cars to the mix: why couldn’t the car take itself out for gas when the driver isn’t using it, or indeed, take itself on other chores like state inspections, oil changes, and scheduled maintenance? And if it does that, how will it pick the supplier?   Sure, the owner could specify in advance, but won’t at least some owners want the car to find the best price on gasoline or respond to special offers such as coupons?

If you do give the car some discretion, how do you know it won’t make choices based on its own preferences?  Perhaps it will favor the gas station that wipes its windshield or gives it a free tire rotation, which you have to suspect feels mighty good to an auto. Indeed, how do you know your car isn't taking Uber jobs on the side, or drag racing with its car friends from the other side of town who you never really liked?  Could the manufacturer have some involvement in this, pocketing that Uber revenue or biasing those purchase decisions in return for payment from suppliers? More generally, when devices become autonomous, do marketers still address their owners or are there ways to sell to things themselves? 

There’s at least a bad science fiction story in all this (“Do self-driving cars pick their own gas stations?” with apologies to Philip K. Dick)., which I naturally proposed to Scott as a short video for the next MarTech conference.  He didn't exactly leap at the chance.

But there are also more serious issues and opportunities to consider. Perhaps interruptive marketing really will be replaced by embedded services and subscriptions which will make product selection and purchase timing decisions without the owners being involved. In some ways, it already happens: think about the choices that a doctor makes when selecting your treatments or building contractor makes when constructing your house. We already know there is plenty of trade advertising to affect those choices. As more decisions get delegated to automated agents, this may be an area we can learn from. But of course, it won’t be exactly the same, so there will be plenty of new approaches to pioneer as well.

This is definitely the kind of discussion to have over drinks. I can’t go into details but rest assured that Scott’s plans for the next MarTech conference do take this into account.

MarTech Conference: Chief Marketing Technology Officers Come Out and Play

I got home late last night from the inaugural two-day MarTech conference in Boston, which was simply terrific. Conference chair Scott Brinker assembled an all-star cast of presenters and, more important, a finely balanced mix of topics from industry trends to practical issues of planning, hiring, organization, and technology choices.  (I guess I should note that I also presented and contributed a few thoughts on the agenda, but credit for the success goes elsewhere.)

While the formal topic of the conference was “marketing technology”, its real theme was “marketing technology leadership”, and in particular emergence of the “chief marketing technology officer” as a critical role. Many attendees held that job, either in title or de facto responsibilities. Most were clearly delighted to find so many other people sharing the same opportunities and challenges. They had probably developed a secret handshake by the time the conference was over, although as a mere consultant I wasn’t told what it was.

The presentations were consistently excellent, which in itself is close to amazing: I guess Scott had checked everyone out carefully before extending his invitations.  Different attendees probably had their own favorites depending on their own interests. That being the case, I think it doesn't insult anyone to say that the two that most resonated with me personally were by Laura McLellan of Gartner – source of the famous “marketing will spend more than IT by 2017” forecast, which she reported has already come true -- and Clorox Director of Marketing Technology Shawn Goodin.

The factoid I recall from McLellan’s presentation was the 81% of large companies already have someone in the chief marketing technologist role – so that particular future had already arrived. My favorite part of Goodin’s talk was a marketing technology capability heat map that displayed all of a company’s tech strengths and weaknesses on one page.

I was also immensely impressed with SapientNitro CTO Sheldon Monteiro’s description of their in-house training program to grow their own chief marketing technology officers – and in particular his response to the objection that people they train might then leave: “What if we don’t train them and they stay?”

The next edition of MarTech is already planned for March 31- April 1 in San Francisco, presumably to be followed by another Boston edition next year. I’m sure they’ll make the obvious extensions like more tracks and pre/post-conference intensive trainings. But why stop there? This is basically summer camp for marketing tech geeks, so I’ve already suggested to Scott that he add audience participation including:

• role-playing: if marketers ran tech and techies ran marketing; if buyers acted like vendors and vendors acted like buyers
• TV show knockoffs: CMTO Shark Tank business plans for marketing technology investments; The Vendor Selection Dating Game; Martech Recruiting Bachelorette; CSI MarTech Unit analyzing project failures; and of course Survivor: CMTO
• board games: CMTO versions of Monopoly, Snakes and Ladders, and Dungeons and Dragons
• scavenger hunt: find the best short list of products via Web research in a fixed period of time, without ever talking to a salesperson
• camp fire stories: vendors share their scariest client experiences, while wearing paper bag masks to protect their jobs
• tall tale telling contest: who can make the most ludicrous claim with a straight face (note: separate divisions for buyers and vendors).
• not to mention a hackathon, talent show, and, karaoke.

Seriously, Scott – who would not pay good money to attend?

-